Shevlin Mark, Murphy Jamie, Dorahy Martin J, Adamson Gary
Psychiatric Epidemiology Research Unit, University of Ulster at Magee College, UK.
Schizophr Res. 2007 Jan;89(1-3):101-9. doi: 10.1016/j.schres.2006.09.014. Epub 2006 Nov 9.
Previous research has suggested that psychosis is better described as a continuum rather than a dichotomous entity. This study aimed to describe the distribution of positive psychosis-like symptoms in the general population by means of latent class analysis.
Latent class analysis was used to identify homogeneous sub-types of psychosis-like experiences. Multinomial logistic regression models were used to interpret the nature of the latent classes, or groups, by estimating the associations with demographic factors, clinical variables, and experiences of traumatic events.
The best fitting latent class model was a four-class solution: a psychosis class, a hallucinatory class, an intermediate class, and a normative class. The associations between the latent classes and the demographic risk factors, clinical variables, and experiences of traumatic events showed significantly higher risks for the psychosis class, the hallucinatory class, and the intermediate class compared to the normative class. Furthermore there appeared to be a grading in the magnitude of the odds ratios: the odds ratios for the psychosis group were generally higher than those for the hallucinatory class, and the odds ratios for the hallucinatory class were generally higher than those for the intermediate class.
The latent class analysis showed that psychosis-like symptoms at the population level could be best explained by four groups that appeared to represent an underlying continuum.
先前的研究表明，精神病更宜被描述为一种连续体，而非二分实体。本研究旨在通过潜在类别分析描述普通人群中阳性精神病性症状的分布情况。
采用潜在类别分析来识别精神病性体验的同质亚型。使用多项逻辑回归模型，通过估计与人口统计学因素、临床变量及创伤性事件经历的关联，来解释潜在类别或组别的性质。
最佳拟合的潜在类别模型为四类解决方案：精神病类别、幻觉类别、中间类别和正常类别。与正常类别相比，潜在类别与人口统计学风险因素、临床变量及创伤性事件经历之间的关联显示，精神病类别、幻觉类别和中间类别具有显著更高的风险。此外，优势比的大小似乎存在分级：精神病组的优势比通常高于幻觉类别，幻觉类别的优势比通常高于中间类别。
潜在类别分析表明，在人群层面，精神病性症状最好由似乎代表潜在连续体的四组来解释。
